2018
DOI: 10.1007/978-1-4614-8265-9_613
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Manoranjan Dash,
Poon Wei Koot

Abstract: Clustering is an important data mining task. Data mining often concerns large and high-dimensional data but unfortunately most of the clustering algorithms in the literature are sensitive to largeness or high-dimensionality or both. Di erent features a ect clusters di erently, some are important for clusters while others may hinder the clustering task. An e cient w ay of handling it is by selecting a subset of important features. It helps in nding clusters e ciently, understanding the data better and reducing …

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